Infrastructure on Autopilot
for AI Agents
Frontend generation gives you momentum.
AutoRail gives you the infrastructure to sustain it.
The Gap Between Prototype and Production
Remember context from three days ago
Stateless agents lose user history between sessions
Orchestrate 50+ concurrent agent tasks
Parallel workflows collapse without proper sequencing
Guarantee failure-safe execution
One failed API call shouldn't cascade through your entire system
Vibe-coding gets you started. It doesn't get you to production.
AutoRail Bridges the Gap
Stateful memory layers
Persistent context that survives sessions, restarts, and scale events
Workflow orchestration
Sequencing, concurrency, retries, and intelligent fallback patterns
Guardrails and rate limiters
Protection against runaway costs, abuse, and cascade failures
Circuit-breaker patterns
Graceful degradation when dependencies fail
Production-grade from day one.
What AutoRail Provisions
Stateful Memory
Persistent context across sessions, workflows, and sub-agents. Your AI remembers everything it needs to—automatically.
Workflow Orchestration
Sequencing, concurrency control, intelligent retries, and fallback patterns. Complex multi-agent workflows that actually work.
Production Guardrails
Rate limiters, circuit breakers, input validation, and policy-as-code. Protection built into every layer.
Deploy Engine
One-click deployment from vibe-coded output to stable runtime. No Docker expertise required.
Observability
Cross-agent traces, structured logs, performance telemetry, and drift detection. See exactly what your agents are doing.
Auto-Scale
Handle multi-agent fan-outs and LLM request bursts automatically. Scale to zero when idle, scale to thousands when needed.
How AutoRail Works
Connect
Point AutoRail at your codebase—whether it's vibe-coded output from Lovable, a LangChain project, or custom agent logic.
Analyze
AutoRail interprets your code structure, identifies agent patterns, and maps infrastructure requirements automatically.
Provision
Backend primitives are generated and deployed—databases, queues, caches, and orchestration layers—all configured for your specific needs.
Monitor
Continuous observability, performance optimization, and drift detection keep your agents running reliably.
No infrastructure expertise required. No configuration files to maintain. Just working production systems.
Built For
Indie Hackers
Ship AI products without becoming an infrastructure expert
Focus on your product, not your backend. AutoRail handles the complexity so you can move fast and stay lean.
Startup Teams
Scale prototypes to production without hiring DevOps
Your engineering team should build features, not fight infrastructure. AutoRail grows with you from MVP to Series A and beyond.
AI Engineers
Production-grade agent systems that actually stay up
You know what good infrastructure looks like. AutoRail implements it automatically—stateful memory, proper orchestration, real observability.
Building a single agent or orchestrating dozens—AutoRail handles the infrastructure so you can focus on what matters.
Launching Soon
We're putting the finishing touches on AutoRail. Bookmark this page to be first in line when we go live.
Early adopters get priority access and direct input on the roadmap.
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